"C# Programming Language Resources" matching MCP servers:

An MCP server that integrates with GitHub Copilot to analyze Axivion static-analysis reports and provide MISRA C:2012 compliance assistance. It offers deep rule explanations, rationale, and confidence-scored fix suggestions for identified code violations.

Enables evaluating Python projects against a deterministic quality bar using analyzer findings, per-dimension scores, and a review verdict, exposed through MCP tools, resources, and prompts. Users can run evaluations, inspect rules, and list analyzers to assess code readiness for review.

Enables AI agents to control a local browser via Playwright's accessibility tree, allowing automated web interactions and testing through natural language commands.

Enables end-to-end testing of CLI applications, REPLs, and TUIs by driving interactive pseudo-terminal sessions and reading clean rendered output through any MCP client.

Enables AI assistants to run code in 24 programming languages on HackerEarth's sandboxed servers and read the printed output or errors, without installing local toolchains. It also lists supported languages with exact identifiers for use when submitting code.

MCP server that exposes Dira ProSuite quality verification to AI assistants, enabling data quality checks on geospatial datasets through natural language.

MCP server for managing test cases, cycles, and results in Zephyr Scale on self-hosted Jira. Enables AI agents to create, search, update, and delete test artifacts through natural language.

Exposes MAID Runner validation tools (validate, snapshot, test) as MCP tools, resources, and prompts for AI agents like Claude Code and Aider, enabling seamless integration with AI development workflows.

Enables LLM agents to programmatically inspect, debug, and test other MCP servers by wrapping the MCP Inspector CLI. Supports listing and calling tools, reading resources, and testing prompts on both local and remote MCP servers.

Audits Excel workbooks by tracing cell dependencies and detecting circular references, volatile functions, and other formula risks, enabling natural-language audit queries on local files.

Turns natural-language API descriptions into runnable k6 load tests, executes them, and returns structured performance metrics for AI-assisted reporting.

Automates visual inspection of development servers by converting natural language test sheets into Playwright scripts and executing them repeatedly.

A high-performance, multi-protocol API mock server with 18 built-in MCP tools for managing HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP mocks, chaos engineering, stateful CRUD resources, and request verification.

Enables LLM agents to run self-healing JMeter performance tests via natural language, from environment setup to capacity discovery and SLO verdict reporting.

Connects AI coding assistants to TestCollab for managing test cases, plans, and suites directly through natural language. It enables users to create, update, and query testing resources within integrated development environments and AI chat clients.

Enables AI assistants to interact with TrafficMorph for load-testing and CI-failure triage, including run management, profile lifecycle, and domain verification through natural language.

Exposes CT's C/C++ verification tools - project setup, analysis, test generation and execution, coverage, reporting - to an MCP client. Requires a local CT 2026.06 or later installation; without one the server reports zero tools.

MCP server that integrates with Testmo to let AI assistants read projects, runs, results, and test cases, and create or update runs, results, and cases via natural language.

Enables editorial content QA over the Model Context Protocol with four local tools that analyze readability, AI-sounding language, SEO on-page factors, and produce full reports where every finding includes an actionable fix.

An MCP server that gives Claude direct control of a real browser via Playwright, enabling AI-driven web testing, autonomous test execution, and live failure analysis through natural language.